Object imaging is useful in a variety of applications. By way of example, biometric recognition systems image biometric objects for authenticating and/or verifying users of devices incorporating the recognition systems. Biometric imaging provides a reliable, non-intrusive way to verify individual identity for recognition purposes. Various types of sensors may be used for biometric imaging.
Fingerprints, like various other biometric characteristics, are based on distinctive personal characteristics and thus provide a reliable mechanism to recognize an individual. Thus, fingerprint sensors have many potential applications. For example, fingerprint sensors may be used to provide access control in stationary applications, such as security checkpoints. Fingerprint sensors may also be used to provide access control in mobile devices, such as cell phones, wearable smart devices (e.g., smart watches and activity trackers), tablet computers, personal data assistants (PDAs), navigation devices, and portable gaming devices. Accordingly, some applications, in particular applications related to mobile devices, may require recognition systems that are both small in size and highly reliable.
Most commercially available fingerprint sensors are based on optical or capacitive sensing technologies. Unfortunately, conventional optical fingerprint sensors are too bulky to be packaged in mobile devices and other common consumer electronic devices, confining their use to door access control terminals and similar applications where sensor size is not a restriction.
As a result, fingerprint sensors in most mobile devices are capacitive sensors having a sensing array configured to sense ridge and valley features of a fingerprint. Typically, these fingerprint sensors either detect absolute capacitance (sometimes known as “self-capacitance”) or trans-capacitance (sometimes known as “mutual capacitance”). In either case, capacitance at each sensing element in the array varies depending on whether a ridge or valley is present, and these variations are electrically detected to form an image of the fingerprint.
While capacitive fingerprint sensors provide certain advantages, most commercially available capacitive fingerprint sensors have difficulty sensing fine ridge and valley features through large distances, requiring the fingerprint to contact a sensing surface that is close to the sensing array. It remains a significant challenge for a capacitive sensor to detect fingerprints through thick layers, such as the thick cover glass (sometimes referred to herein as a “cover lens”) that protects the display of many smart phones and other mobile devices. To address this issue, a cutout is often formed in the cover glass in an area beside the display, and a discrete capacitive fingerprint sensor (often integrated with a mechanical button) is placed in the cutout area so that it can detect fingerprints without having to sense through the cover glass. The need for a cutout makes it difficult to form a flush surface on the face of device, detracting from the user experience, and complicating the manufacture. The existence of mechanical buttons also takes up valuable device real estate.
One possible solution for an optical based sensor is to use a pinhole type camera. A pinhole camera includes a thin light blocking layer with a small aperture. Light from an object on one side of the blocking layer passes through the aperture and is projected in an inverted fashion onto a detection surface disposed on the opposite side of the blocking layer. However, pinhole cameras suffer from certain disadvantages. For example, images collected from a pinhole camera arrangement are inverted and thus may require additional processing to be useful. Moreover, the vast amount of light from the object is blocked by the blocking layer and only a small amount of light is transmitted through the aperture. Thus, image quality may be an issue. Moreover, the area of the object imaged varies significantly as the distance between the blocking layer and the object to be imaged varies.